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Empirical analysis of pig welfare levels and their impact on pig breeding efficiency—Based on 773 pig farmers’ survey data

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  • Yanling Li
  • Nanjun Wu
  • Rong Xu
  • Liqing Li
  • Wei Zhou
  • Xianjun Zhou

Abstract

Few studies of the pig production efficiency are from the perspective of animal welfare. Therefore, this study conducted a comprehensive evaluation of pig welfare levels based on survey data from 773 pig farmers from 23 counties in the Chinese provinces of Hunan, Zhejiang, Guangdong, Guizhou, and Shanxi. This study used the Delphi method, Analytic Hierarchy Process (AHP), and Data Envelopment Analysis (DEA)-Tobit regression model to analyze farmers’ pig production efficiency and its influencing factors. This paper found that most farmers’ pig production efficiency is low, and the DEA is invalid. Only 2.9% of pig farmers’ who breed pigs are at the optimal level in terms of welfare, and their production efficiency is relatively high. In contrast, 49.34% of the farmers are at the medium welfare level, and compared with the farmers at the optimal welfare level, these farmers’ pig production efficiency is low. Additionally, the farmers’ age, gender, and number of years of experience with pig breeding have a significant effect. Furthermore, the scale of pig breeding and feeding type, the agriculture facilities for the central treatment of waste in local areas, and the availability of local agricultural science and technology personnel have a considerable influence on pig production efficiency.

Suggested Citation

  • Yanling Li & Nanjun Wu & Rong Xu & Liqing Li & Wei Zhou & Xianjun Zhou, 2017. "Empirical analysis of pig welfare levels and their impact on pig breeding efficiency—Based on 773 pig farmers’ survey data," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-11, December.
    • Handle: RePEc:plo:pone00:0190108
    DOI: 10.1371/journal.pone.0190108
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    References listed on IDEAS

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    1. Tonsor, Glynn T. & Wolf, Christopher A., 2011. "On mandatory labeling of animal welfare attributes," Food Policy, Elsevier, vol. 36(3), pages 430-437, June.
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    1. Stefano Duglio & Alessandro Bonadonna & Marilisa Letey & Giovanni Peira & Laura Zavattaro & Giampiero Lombardi, 2019. "Tourism Development in Inner Mountain Areas—The Local Stakeholders’ Point of View through a Mixed Method Approach," Sustainability, MDPI, vol. 11(21), pages 1-19, October.
    2. Zhong, Shen & Li, Junwei & Chen, Xi & Wen, Hongmei, 2022. "A multi-hierarchy meta-frontier approach for measuring green total factor productivity: An application of pig breeding in China," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    3. Aijun Guo & Xiaoyun Wei & Fanglei Zhong & Penglong Wang & Xiaoyu Song, 2022. "Does Cognition of Resources and the Environment Affect Farmers’ Production Efficiency? Study of Oasis Agriculture in China," Agriculture, MDPI, vol. 12(5), pages 1-18, April.

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